---
base_model: google/paligemma-3b-pt-224
library_name: peft
license: gemma
tags:
- generated_from_trainer
model-index:
- name: paligemma-cnmc-ft
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# paligemma-cnmc-ft

This model is a fine-tuned version of [google/paligemma-3b-pt-224](https://huggingface.co./google/paligemma-3b-pt-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1871

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 170
- num_epochs: 100

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| No log        | 0.9645  | 17   | 1.4372          |
| No log        | 1.9858  | 35   | 1.1505          |
| 1.1745        | 2.9504  | 52   | 0.6419          |
| 1.1745        | 3.9716  | 70   | 0.3542          |
| 1.1745        | 4.9929  | 88   | 0.3141          |
| 0.3853        | 5.9574  | 105  | 0.2847          |
| 0.3853        | 6.9787  | 123  | 0.2544          |
| 0.3853        | 8.0     | 141  | 0.2498          |
| 0.2598        | 8.9645  | 158  | 0.2074          |
| 0.2598        | 9.9858  | 176  | 0.1840          |
| 0.2598        | 10.9504 | 193  | 0.1656          |
| 0.1867        | 11.9716 | 211  | 0.1665          |
| 0.1867        | 12.9929 | 229  | 0.1719          |
| 0.1867        | 13.9574 | 246  | 0.1871          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.43.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1